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- W2379735252 abstract "In this paper,an improved method is proposed to overcome the shortcomings of conventional method of surface-related multiple elimination(SRME).Firstly,multiple model is predicted by data correlation and iterative update.The method can decrease the rigorous requirement of input data,however,which is needed in the method of SRME.Moreover,it can also improve the suitability of input data sets with near-offset deficiency or spatial aliasing.Secondly,a non-causal and non-stationary matching filter is designed,which can process an entire multiple model trace.In addition,even if the time of predictive multiple model is later than the actual multiple,the method still works well.Finally,applying the method to synthetical and field data sets indicates the superiority in multiple model prediction and matching subtraction." @default.
- W2379735252 created "2016-06-24" @default.
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- W2379735252 date "2013-01-01" @default.
- W2379735252 modified "2023-09-26" @default.
- W2379735252 title "Non-causal matching filter multiple elimination method based on correlation and iteration" @default.
- W2379735252 hasPublicationYear "2013" @default.
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